Multicomponent Signal Unmixing from Nanoheterostructures: Overcoming the Traditional Challenges of Nanoscale X-ray Analysis via Machine Learning

نویسندگان

  • David Rossouw
  • Pierre Burdet
  • Francisco de la Peña
  • Caterina Ducati
  • Benjamin R. Knappett
  • Andrew E. H. Wheatley
  • Paul A. Midgley
چکیده

The chemical composition of core-shell nanoparticle clusters have been determined through principal component analysis (PCA) and independent component analysis (ICA) of an energy-dispersive X-ray (EDX) spectrum image (SI) acquired in a scanning transmission electron microscope (STEM). The method blindly decomposes the SI into three components, which are found to accurately represent the isolated and unmixed X-ray signals originating from the supporting carbon film, the shell, and the bimetallic core. The composition of the latter is verified by and is in excellent agreement with the separate quantification of bare bimetallic seed nanoparticles.

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عنوان ژورنال:

دوره 15  شماره 

صفحات  -

تاریخ انتشار 2015